755 resultados para Health education. Popular health education. Group diabetes Mellitus.
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OBJECTIVE: To assess the effect of a health promotion program on cardiometabolic risk profile in Japanese-Brazilians. METHODS: A total of 466 subjects from a study on diabetes prevalence conducted in the city of Bauru, southeastern Brazil, in 2000 completed a 1-year intervention program (2005-2006) based on healthy diet counseling and physical activity. Changes in blood pressure and metabolic parameters in the 2005-2006 period were compared with annual changes in these same variables in the 2000-2005 period. RESULTS: During the intervention, there were greater annual reductions in mean (SD) waist circumference [-0.5(3.8) vs. 1.2(1.2) cm per year, p<0.001], systolic blood pressure [-4.6(17.9) vs. 1.8(4.3) mmHg per year, p<0.001], 2-hour plasma glucose [-1.2(2.1) vs. -0.2(0.6) mmol/L per year, p<0.001], LDL-cholesterol [-0.3(0.9) vs. -0.1(0.2) mmol/L per year, p<0.001] and Framingham coronary heart disease risk score [-0.25(3.03) vs. 0.11(0.66) per year, p=0.02] but not in triglycerides [0.2(1.6) vs. 0.1(0.42) mmol/L per year, p<0.001], and fasting insulin level [1.2(5.8) vs. -0.7(2.2) IU/mL per year, p<0.001] compared with the pre-intervention period. Significant reductions in the prevalence of impaired fasting glucose/impaired glucose tolerance and diabetes were seen during the intervention (from 58.4% to 35.4%, p<0.001; and from 30.1% to 21.7%, p= 0.004, respectively). CONCLUSIONS: A one-year community-based health promotion program brings cardiometabolic benefits in a high-risk population of Japanese-Brazilians.
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PRINCIPLES We aimed to evaluate the efficacy of, and treatment satisfaction with, insulin glargine administered with SoloSTAR® or ClikSTAR® pens in patients with type 2 diabetes mellitus managed by primary care physicians in Switzerland. METHODS A total of 327 patients with inadequately controlled type 2 diabetes were enrolled by 72 physicians in this prospective observational study, which aimed to evaluate the efficacy of a 6-month course of insulin glargine therapy measured as development of glycaemic control (glycosylated haemoglobin [HbA1c] and fasting plasma glucose [FPG]) and weight change. We also assessed preference for reusable or disposable pens, and treatment satisfaction. RESULTS After 6 months, the mean daily dose of insulin glargine was 27.7±14.3 U, and dose titration was completed in 228 (72.4%) patients. Mean HbA1c decreased from 8.9%±1.6% (n=327) to 7.3%±1.0% (n=315) (p<0.0001), and 138 (43.8%) patients achieved an HbA1c≤7.0%. Mean FPG decreased from 10.9±4.5 to 7.3±1.8 mmol/l (p<0.0001). Mean body weight did not change (85.4±17.2 kg vs 85.0±16.5 kg; p=0.11). Patients' preference was in favour of the disposable SoloStar® pen (80%), as compared with the reusable ClickStar® pen (20%). Overall, 92.6% of physicians and 96.3% of patients were satisfied or very satisfied with the insulin glargine therapy. CONCLUSIONS In patients with type 2 diabetes insulin glargine administered by SoloSTAR® or ClikSTAR® pens, education on insulin injection and on self-management of diabetes was associated with clinically meaningful improvements in HbA1c and FPG without a mean collective weight gain. The vast majority of both patients and primary care physicians were satisfied with the treatment intensification.
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The level of compliance with clinical practice guidelines for patients with Type II Diabetes Mellitus was evaluated in 157 patients treated at BAMC from 1 January 2006 to 1 January 2007. This retrospective analysis was conducted reviewing data from medical records and following the VA/DOD protocols that health care providers are expected to follow at this facility. Data collected included patient’s age and gender, presence or absence of complications of diabetes, physical examination findings, glycemic and lipid control, eye care, foot care, kidney function, and self-management and education. Subjects were selected performing systematic random sampling, and included both male and female patients, from a variety of ages and ethnic groups. The Diabetes complications screened for included glycemic and lipid complications, retinopathy, cardiovascular complications, peripheral circulation complications, and nephropathy. The results revealed that 19.10% had no complications and that the most common complications were: cardiovascular (49.68%), glycemic and lipid control (10.82%), retinopathy and peripheral circulation (8.28% each), and nephropathy (2.54%). Only 2.54% of the records reviewed did not include information on complications. Strictly following the Department of Defense guidelines, six treatment modules were evaluated independently and together to get a final percentage of adherence to the clinical practice guidelines. It was established that the level of adherence was going to be graded as follows: Extremely deficient: 0-15%; very poor: 16-30%; Poor and in need of improvement: 31-45%. Acceptable: 46-60%; Good: 61-80%, and Excellent: 81-100%. The results indicated that the percentage of physicians' adherence to each protocol was as follows: 88.31%, 89.93%, 90.63%, 89.42%, 89.42% and 89.64%. When the results were pooled, the level of adherence to the clinical practice guidelines was 89.55%, proving my hypothesis that Brooke Army Medical Center physicians have excellent adherence to the standard protocols for Diabetes Type II to treat their patients. ^
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This thesis presents an analysis of data from Molecular Epidemiology of Type II Diabetes Mellitus in Mexican Americans. The study included 294 families. Among the participating families were 500 Mexican American females aged 19 to 86 who provided information on characteristics such as height, weight, and a variety of biochemical indicators. The research questions for this thesis are: (1) How strong is the association between indicators of the metabolic syndrome in study participants and their family histories of type II diabetes; and (2) How is an individual's family history of type II diabetes, age and socioeconomic status associated with the metabolic syndrome? In this thesis education status of the participants is used as an indicator of socioeconomic status. Answers to these questions are provided through the analysis of women's responses to written questionnaires and biochemical data. ^
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En todo el mundo se ha observado un crecimiento exponencial en la incidencia de enfermedades crónicas como la hipertensión y enfermedades cardiovasculares y respiratorias, así como la diabetes mellitus, que causa un número de muertes cada vez mayor en todo el mundo (Beaglehole et al., 2008). En concreto, la prevalencia de diabetes mellitus (DM) está aumentando de manera considerable en todas las edades y representa un serio problema de salud mundial. La diabetes fue la responsable directa de 1,5 millones de muertes en 2012 y 89 millones de años de vida ajustados por discapacidad (AVAD) (OMS, 2014). Uno de los principales dilemas que suelen asociarse a la gestión de EC es la adherencia de los pacientes a los tratamientos, que representa un aspecto multifactorial que necesita asistencia en lo relativo a: educación, autogestión, interacción entre los pacientes y cuidadores y compromiso de los pacientes. Medir la adherencia del tratamiento es complicado y, aunque se ha hablado ampliamente de ello, aún no hay soluciones “de oro” (Reviews, 2002). El compromiso de los pacientes, a través de la participación, colaboración, negociación y a veces del compromiso firme, aumentan las oportunidades para una terapia óptima en la que los pacientes se responsabilizan de su parte en la ecuación de adherencia. Comprometer e involucrar a los pacientes diabéticos en las decisiones de su tratamiento, junto con expertos profesionales, puede ayudar a favorecer un enfoque centrado en el paciente hacia la atención a la diabetes (Martin et al., 2005). La motivación y atribución de poder de los pacientes son quizás los dos factores interventores más relevantes que afectan directamente a la autogestión de la atención a la diabetes. Se ha demostrado que estos dos factores desempeñan un papel fundamental en la adherencia a la prescripción, así como en el fomento exitoso de un estilo de vida sana y otros cambios de conducta (Heneghan et al., 2013). Un plan de educación personalizada es indispensable para proporcionarle al paciente las herramientas adecuadas que necesita para la autogestión efectiva de la enfermedad (El-Gayar et al. 2013). La comunicación efectiva es fundamental para proporcionar una atención centrada en el paciente puesto que influye en las conductas y actitudes hacia un problema de salud ((Frampton et al. 2008). En este sentido, la interactividad, la frecuencia, la temporalización y la adaptación de los mensajes de texto pueden promover la adherencia a un régimen de medicación. Como consecuencia, adaptar los mensajes de texto a los pacientes puede resultar ser una manera de hacer que las sugerencias y la información sean más relevantes y efectivas (Nundy et al. 2013). En este contexto, las tecnologías móviles en el ámbito de la salud (mHealth) están desempeñando un papel importante al conectar con pacientes para mejorar la adherencia a medicamentos recetados (Krishna et al., 2009). La adaptación de los mensajes de texto específicos de diabetes sigue siendo un área de oportunidad para mejorar la adherencia a la medicación y ofrecer motivación a adultos con diabetes. Sin embargo, se necesita más investigación para entender totalmente su eficacia. Los consejos de texto personalizados han demostrado causar un impacto positivo en la atribución de poder a los pacientes, su autogestión y su adherencia a la prescripción (Gatwood et al., 2014). mHealth se puede utilizar para ofrecer programas de asistencia de autogestión a los pacientes con diabetes y, al mismo tiempo, superar las dificultades técnicas y financieras que supone el tratamiento de la diabetes (Free at al., 2013). El objetivo principal de este trabajo de investigación es demostrar que un marco tecnológico basado en las teorías de cambios de conducta, aplicado al campo de la mHealth, permite una mejora de la adherencia al tratamiento en pacientes diabéticos. Como método de definición de una solución tecnológica, se han adoptado un conjunto de diferentes técnicas de conducta validadas denominado marco de compromiso de retroacción conductual (EBF, por sus siglas en inglés) para formular los mensajes, guiar el contenido y evaluar los resultados. Los estudios incorporan elementos del modelo transteórico (TTM, por sus siglas en inglés), la teoría de la fijación de objetivos (GST, por sus siglas en inglés) y los principios de comunicación sanitaria persuasiva y eficaz. Como concepto general, el modelo TTM ayuda a los pacientes a progresar a su próxima fase de conducta a través de mensajes de texto motivados específicos y permite que el médico identifique la fase actual y adapte sus estrategias individualmente. Además, se adoptan las directrices del TTM para fijar objetivos personalizados a un nivel apropiado a la fase de cambio del paciente. La GST encierra normas que van a ponerse en práctica para promover la intervención educativa y objetivos de pérdida de peso. Finalmente, los principios de comunicación sanitaria persuasiva y eficaz aplicados a la aparición de los mensajes se han puesto en marcha para aumentar la efectividad. El EBF tiene como objetivo ayudar a los pacientes a mejorar su adherencia a la prescripción y encaminarlos a una mejora general en la autogestión de la diabetes mediante mensajes de texto personalizados denominados mensajes de retroacción automáticos (AFM, por sus siglas en inglés). Después de una primera revisión del perfil, consistente en identificar características significativas del paciente basadas en las necesidades de tratamiento, actitudes y conductas de atención sanitaria, el sistema elige los AFM personalizados, los aprueba el médico y al final se transfieren a la interfaz del paciente. Durante el tratamiento, el usuario recopila los datos en dispositivos de monitorización de pacientes (PMD, por sus siglas en inglés) de una serie de dispositivos médicos y registros manuales. Los registros consisten en la toma de medicación, dieta y actividad física y tareas de aprendizaje y control de la medida del metabolismo. El compromiso general del paciente se comprueba al estimar el uso del sistema y la adherencia del tratamiento y el estado de los objetivos del paciente a corto y largo plazo. El módulo de análisis conductual, que consiste en una serie de reglas y ecuaciones, calcula la conducta del paciente. Tras lograr el análisis conductual, el módulo de gestión de AFM actualiza la lista de AFM y la configuración de los envíos. Las actualizaciones incluyen el número, el tipo y la frecuencia de mensajes. Los AFM los revisa periódicamente el médico que también participa en el perfeccionamiento del tratamiento, adaptado a la fase transteórica actual. Los AFM se segmentan en distintas categorías y niveles y los pacientes pueden ajustar la entrega del mensaje de acuerdo con sus necesidades personales. El EBF se ha puesto en marcha integrado dentro del sistema METABO, diseñado para facilitar al paciente diabético que controle sus condiciones relevantes de una manera menos intrusiva. El dispositivo del paciente se vincula en una plataforma móvil, mientras que una interfaz de panel médico permite que los profesionales controlen la evolución del tratamiento. Herramientas específicas posibilitan que los profesionales comprueben la adherencia del paciente y actualicen la gestión de envíos de AFM. El EBF fue probado en un proyecto piloto controlado de manera aleatoria. El principal objetivo era examinar la viabilidad y aceptación del sistema. Los objetivos secundarios eran también la evaluación de la eficacia del sistema en lo referente a la mejora de la adherencia, el control glucémico y la calidad de vida. Se reclutaron participantes de cuatro centros clínicos distintos en Europa. La evaluación del punto de referencia incluía datos demográficos, estado de la diabetes, información del perfil, conocimiento de la diabetes en general, uso de las plataformas TIC, opinión y experiencia con dispositivos electrónicos y adopción de buenas prácticas con la diabetes. La aceptación y eficacia de los criterios de evaluación se aplicaron para valorar el funcionamiento del marco tecnológico. El principal objetivo era la valoración de la eficacia del sistema en lo referente a la mejora de la adherencia. En las pruebas participaron 54 pacientes. 26 fueron asignados al grupo de intervención y equipados con tecnología móvil donde estaba instalado el EBF: 14 pacientes tenían T1DM y 12 tenían T2DM. El grupo de control estaba compuesto por 25 pa cientes que fueron tratados con atención estándar, sin el empleo del EBF. La intervención profesional tanto de los grupos de control como de intervención corrió a cargo de 24 cuidadores, entre los que incluían diabetólogos, nutricionistas y enfermeras. Para evaluar la aceptabilidad del sistema y analizar la satisfacción de los usuarios, a través de LimeSurvey, se creó una encuesta multilingüe tanto para los pacientes como para los profesionales. Los resultados también se recopilaron de los archivos de registro generados en los PMD, el panel médico profesional y las entradas de la base de datos. Los mensajes enviados hacia y desde el EBF y los archivos de registro del sistema y los servicios de comunicación se grabaron durante las cinco semanas del estudio. Se entregaron un total de 2795 mensajes, lo que supuso una media de 107,50 mensajes por paciente. Como se muestra, los mensajes disminuyen con el tiempo, indicando una mejora global de la adherencia al plan de tratamiento. Como se esperaba, los pacientes con T1DM recibieron más consejos a corto plazo, en relación a su estado. Del mismo modo, al ser el centro de T2DM en cambios de estilo de vida sostenible a largo plazo, los pacientes con T2DM recibieron más consejos de recomendación, en cuanto a dietas y actividad física. También se ha llevado a cabo una comparación de la adherencia e índices de uso para pacientes con T1DM y T2DM, entre la primera y la segunda mitad de la prueba. Se han observado resultados favorables para el uso. En lo relativo a la adherencia, los resultados denotaron una mejora general en cada dimensión del plan de tratamiento, como la nutrición y las mediciones de inserción de glucosa en la sangre. Se han llevado a cabo más estudios acerca del cambio a nivel educativo antes y después de la prueba, medidos tanto para grupos de control como de intervención. Los resultados indicaron que el grupo de intervención había mejorado su nivel de conocimientos mientras que el grupo de control mostró una leve disminución. El análisis de correlación entre el nivel de adherencia y las AFM ha mostrado una mejora en la adherencia de uso para los pacientes que recibieron los mensajes de tipo alertas, y unos resultados no significativos aunque positivos relacionados con la adherencia tanto al tratamiento que al uso correlacionado con los recordatorios. Por otra parte, los AFM parecían ayudar a los pacientes que no tomaban suficientemente en serio su tratamiento en el principio y que sí estaban dispuestos a responder a los mensajes recibidos. Aun así, los pacientes que recibieron demasiadas advertencias, comenzaron a considerar el envío de mensajes un poco estresante. El trabajo de investigación llevado a cabo al desarrollar este proyecto ofrece respuestas a las cuatro hipótesis de investigación que fueron la motivación para el trabajo. • Hipótesis 1 : es posible definir una serie de criterios para medir la adherencia en pacientes diabéticos. • Hipótesis 2: es posible diseñar un marco tecnológico basado en los criterios y teorías de cambio de conducta mencionados con anterioridad para hacer que los pacientes diabéticos se comprometan a controlar su enfermedad y adherirse a planes de atención. • Hipótesis 3: es posible poner en marcha el marco tecnológico en el sector de la salud móvil. • Hipótesis 4: es posible utilizar el marco tecnológico como solución de salud móvil en un contexto real y tener efectos positivos en lo referente a indicadores de control de diabetes. La verificación de cada hipótesis permite ofrecer respuesta a la hipótesis principal: La hipótesis principal es: es posible mejorar la adherencia diabética a través de un marco tecnológico mHealth basado en teorías de cambio de conducta. El trabajo llevado a cabo para responder estas preguntas se explica en este trabajo de investigación. El marco fue desarrollado y puesto en práctica en el Proyecto METABO. METABO es un Proyecto I+D, cofinanciado por la Comisión Europea (METABO 2008) que integra infraestructura móvil para ayudar al control, gestión y tratamiento de los pacientes con diabetes mellitus de tipo 1 (T1DM) y los que padecen diabetes mellitus de tipo 2 (T2DM). ABSTRACT Worldwide there is an exponential growth in the incidence of Chronic Diseases (CDs), such as: hypertension, cardiovascular and respiratory diseases, as well as diabetes mellitus, leading to rising numbers of deaths worldwide (Beaglehole et al. 2008). In particular, the prevalence of diabetes mellitus (DM) is largely increasing among all ages and constitutes a major worldwide health problem. Diabetes was directly responsible for 1,5 million deaths in 2012 and 89 million Disability-adjusted life year (DALYs) (WHO 2014). One of the key dilemmas often associated to CD management is the patients’ adherence to treatments, representing a multi-factorial aspect that requires support in terms of: education, self-management, interaction between patients and caregivers, and patients’ engagement. Measuring adherence is complex and, even if widely discussed, there are still no “gold” standards ((Giardini et al. 2015), (Costa et al. 2015). Patient’s engagement, through participation, collaboration, negotiation, and sometimes compromise, enhance opportunities for optimal therapy in which patients take responsibility for their part of the adherence equation. Engaging and involving diabetic patients in treatment decisions, along with professional expertise, can help foster a patient-centered approach to diabetes care (Martin et al. 2005). Patients’ motivation and empowerment are perhaps the two most relevant intervening factors that directly affect self-management of diabetes care. It has been demonstrated that these two factors play an essential role in prescription adherence, as well as for the successful encouragement of a healthy life-style and other behavioural changes (Heneghan et al. 2013). A personalised education plan is indispensable in order to provide the patient with the appropriate tools needed for the effective self-management of the disease (El-Gayar et al. 2013). Effective communication is at the core of providing patient-centred care since it influences behaviours and attitudes towards a health problem (Frampton et al. 2008). In this regard, interactivity, frequency, timing, and tailoring of text messages may promote adherence to a medication regimen. As a consequence, tailoring text messages to patients can constitute a way of making suggestions and information more relevant and effective (Nundy et al. 2013). In this context, mobile health technologies (mHealth) are playing significant roles in improving adherence to prescribed medications (Krishna et al. 2009). The tailoring of diabetes-specific text messages remains an area of opportunity to improve medication adherence and provide motivation to adults with diabetes but further research is needed to fully understand their effectiveness. Personalized text advices have proven to produce a positive impact on patients’ empowerment, self-management, and adherence to prescriptions (Gatwood et al. 2014). mHealth can be used for offering self-management support programs to diabetes patients and at the same time surmounting the technical and financial difficulties involved in diabetes treatment (Free et al. 2013). The main objective of this research work is to demonstrate that a technological framework, based on behavioural change theories, applied to mHealth domain, allows improving adherence treatment in diabetic patients. The framework, named Engagement Behavioural Feedback Framework (EBF), is built on top of validated behavioural techniques to frame messages, guide the definition of contents and assess outcomes: elements from the Transtheoretical Model (TTM), the Goal-Setting Theory (GST), Effective Health Communication (EHC) guidelines and Principles of Persuasive Technology (PPT) were incorporated. The TTM helps patients to progress to a next behavioural stage, through specific motivated text messages, and allow clinician’s identifying the current stage and tailor its strategies individually. Moreover, TTM guidelines are adopted to set customised goals at a level appropriate to the patient’s stage of change. The GST was used to build rules to be applied for enhancing educational intervention and weight loss objectives. Finally, the EHC guidelines and the PPT were applied to increase the effectiveness of messages. The EBF aims to support patients on improving their prescription adherence and persuade them towards a general improvement in diabetes self-management, by means of personalised text messages, named Automatic Feedback Messages (AFM). After a first profile screening, consisting in identifying meaningful patient characteristics based on treatment needs, attitudes and health care behaviours, customised AFMs are selected by the system, approved by the professional, and finally transferred into the patient interface. During the treatment, the user collects the data into a Patient Monitoring Device (PMD) from a set of medical devices and from manual inputs. Inputs consist in medication intake, diet and physical activity, metabolic measurement monitoring and learning tasks. Patient general engagement is checked by estimating the usage of the system and the adherence of treatment and patient goals status in the short and the long term period. The Behavioural Analysis Module, consisting in a set of rules and equations, calculates the patient’s behaviour. After behavioural analysis is accomplished, the AFM library and the dispatch setting are updated by the AFM Manager module. Updates include the number, the type and the frequency of messages. The AFMs are periodically supervised by the professional who also participates to the refinement of the treatment, adapted to the current transtheoretical stage. The AFMs are segmented in different categories and levels and patients can adjust message delivery in accordance with their personal needs. The EBF was integrated to the METABO system, designed to facilitate diabetic patients in managing their disease in a less intrusive approach. Patient device corresponds in a mobile platform, while a medical panel interface allows professionals to monitoring the treatment evolution. Specific tools allow professional to check patient adherence and to update the AFMs dispatch management. The EBF was tested in a randomised controlled pilot. The main objective was to examine the feasibility and acceptance of the system. Secondary objectives were also the assessment of the effectiveness of system in terms of adherence improvement, glycaemic control, and quality of life. Participants were recruited from four different clinical centres in Europe. The baseline assessment included demographics, diabetes status, profile information, knowledge about diabetes in general, usage of ICT platforms, opinion and experience about electronic devices and adoption of good practices with diabetes. Acceptance and the effectiveness evaluation criteria were applied to evaluate the performance of the technological framework. The main objective was the assessment of the effectiveness of system in terms of adherence improvement. Fifty-four patients participated on the trials. Twenty-six patients were assigned in the intervention group and equipped with mobile where the EBF was installed: 14 patients were T1DM and 12 were T2DM. The control group was composed of 25 patients that were treated through a standard care, without the usage of the EBF. Professional’s intervention for both intervention and control groups was carried out by 24 care providers, including endocrinologists, nutritionists, and nurses. In order to evaluate the system acceptability and analyse the users’ satisfaction, an online multi-language survey, using LimeSurvey, was produced for both patients and professionals. Results were also collected from the log-files generated in the PMDs, the professional medical panel and the entries of the data base. The messages sent to and from the EBF and the log-files of the system and communication services were recorded over 5 weeks of the study. A total of 2795 messages were submitted, representing an average of 107,50 messages per patient. As demonstrated, messages decrease over time indicating an overall improvement of the care plan’s adherence. As expected, T1DM patients were more loaded with short-term advices, in accordance with their condition. Similarly, being the focus of T2DM on long-term sustainable lifestyle changes, T2DM received more reminders advices, as for diet and physical activity. Favourable outcomes were observed for treatment and usage adherences of the intervention group: for both the adherence indices, results denoted a general improvement on each care plan’s dimension, such as on nutrition and blood glucose input measurements. Further studies were conducted on the change on educational level before and after the trial, measured for both control and intervention groups. The outcomes indicated the intervention group has improved its level of knowledge, while the control group denoted a low decrease. The correlation analysis between the level of adherences and the AFMs showed an improvement in usage adherence for patients who received warnings message, while non-significantly yet even positive indicators related to both treatment and usage adherence correlated with the Reminders. Moreover, the AFMs seemed to help those patients who did not take their treatment seriously enough in the beginning and who were willing to respond to the messages they received. Even though, patients who received too many Warnings, started to consider the message dispatch to be a bit stressful. The research work carried out in developing this research work provides responses to the four research hypothesis that were the motivation for the work: •Hypothesis 1: It is possible to define a set of criteria to measure adherence in diabetic patients. •Hypothesis 2: It is possible to design a technological framework, based on the aforementioned criteria and behavioural change theories, to engage diabetic patients in managing their disease and adhere to care plans. •Hypothesis 3: It is possible to implement the technological framework in the mobile health domain. •Hypothesis 4: It is possible to use the technological framework as a mobile health solution in a real context and have positive effects in terms of diabetes management indicators. The verification of each hypothesis allowed us to provide a response to the main hypothesis: The Main Hypothesis is: It is possible to improve diabetic adherence through a mHealth technological framework based on behavioural change theories. The work carried out to answer these questions is explained in this research work. The framework was developed and applied in the METABO project. METABO is an R&D project, co-funded by the European Commission (METABO 2008) that integrates mobile infrastructure for supporting the monitoring, management, and treatment of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients.
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"The National diabetes mellitus research and education act (Public law 93-354)": v. 1, p. 93-97.
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Thesis (Master's)--University of Washington, 2016-06
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OBJECTIVE - To assess the performance of health systems using diabetes as a tracer condition. RESEARCH DESIGN AND METHODS - We generated a measure of case-fatality among young people with diabetes Using the mortalily-to-incidence ratio (M/I ratio) for 29 industrialized countries using published data on diabetes incidence and mortality. Standardized incidence rates for ages 0-14 years were extracted from the World Health Organization DiaMond Study for the period 1990-1994; data on death from diabetes for ages 0-39 years were obtained from the World Health Organization Mortality database and converted into age-standardized death rates for the period 1994-1998, using the European standard population. RESULTS - The MA ratio varied > 10-fold. These relative differences appear similar to those observed in cohort studies of mortality among young people with type I diabetes in five countries. A sensitivity analysis showed that using plausible assumptions about potential overestimation of diabetes as a cause of death and underestimation of incidence rates in the U.S. yields an M/I ratio that would still be twice as high as in the U.K. or Canada. CONCLUSIONS - The M/I ratio for diabetes provides a means of differentiating countries on quality of care for people with diabetes. It is solely an indicator of potential problems, a basis for Stimulating more detailed assessments of whether such problems exist, and what can be done to address them.
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Diabetes mellitus is a condition which requires a high degree of patient cooperation in self-management to achieve optimal glycaemic control. The concept of patient education, to enhance the treatment and management of diabetes, is well recognised. Several diabetes education programmes have already been described, but increased knowledge of diabetes did not necessarily result in improved self-mangement or glycaemic control. Other factors, such as attitudes and motivations, may therefore be particuarly important. The aims of the present study were to investigate the influence of patients' attitudes to diabetes, and to develop motivational aspects which enable the application of knowledge to enhance self-management and compliance with treatment. Thirty-one insulin-dependent diabetic (IDD) patients entered into a 12 month educational programme, particularly designed to increase motivation. Patients' attitudes to diabetes, their knowledge and self-management skills were assessed using questionnaires and practical tests, and parameters of glycaemic control were measured. The progress of these patients was compared at intervals with a close matched group of 25 control IFF patients who continued to receive routine clinic care. Patients completing the educational programme achieved better glycaemic control (p< 0.05), greater knowledge (p< 0.001), more favourable attitudes (p< 0.03) and increased competence in management skills (p< 0.02) compared with the control group. Evaluation procedures indicated that the programme was acceptable to the patients, and was successful in terms of increasing patient motivation. Six months after completion of the programme, glycaemic control deteriorated, although knowledge, attitudes and management skills were unchanged. This might reflect the withdrawal of extrinsic motivation, attention and supervision provided during the programme. It is recommended that consideration be given to the development of patients' intrinsic motivation to achieve maximum benefit from diabetes education programmes.
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Objectives: We investigated the relationship among factors predicting inadequate glucose control among 182 Cuban-American adults (Females=110, Males=72) with type 2 diabetes mellitus (CAA). Study Design: Cross-sectional study of CAA from a randomized mailing list in two counties of South Florida Methods: Fasted blood parameters and anthropometric measures were collected during the study. BMI was calculated (kg/ m2). Characteristics and diabetes care of CAA were self-reported Participants were screened by trained interviewers for heritage and diabetes status (inclusion criteria: self-reported having type 2 diabetes; age 35 years, male and female; not pregnant or lactating; no thyroid disorders; no major psychiatric disorders). Participants signed informed consent form. Statistical analyses used SPSS and included descriptive statistic, multiple logistic and ordinal logistic regression models, where all CI 95%. Results: Eighty-eight percent of CAA had BMI of ≥ 25 kg/ m2. Only 54% reported having a diet prescribed/told to schedule meals. We found CAA told to schedule meals were 3.62 more likely to plan meals (1.81, 7.26), p<0.001) and given a prescribed diet, controlling for age, corresponded with following a meal plan OR 4.43 (2.52, 7.79, p<0.001). The overall relationship for HbA1c < 8.5 to following a meal plan was OR 9.34 (2.84, 30.7. p<0.001). Conclusions: The advantage of having a medical professional prescribe a diet seems to be an important environmental support factor in this sample’s diabetes care, since obesity rates are well above the national average. Nearly half CAA are not given dietary guidance, yet our results indicate CAA may improve glycemic control by receiving dietary instructions.
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Acknowledgment MN's PhD scholarship was provided by Ministry of Health and Medical Education (Islamic Republic of Iran). This study was funded by the University of Aberdeen. FFS is funded by Fuse, the UK Clinical Research Collaboration Centre of Excellence for Translational Research in Public Health. The researchers gratefully acknowledge all the Type 2 diabetic patients and their household members who participated in the study for their contribution to this study; without them there would be no data. The researchers gratefully acknowledge the SDRN for providing the list of Type 2 diabetes and helping for sampling.
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Acknowledgment MN's PhD scholarship was provided by Ministry of Health and Medical Education (Islamic Republic of Iran). This study was funded by the University of Aberdeen. FFS is funded by Fuse, the UK Clinical Research Collaboration Centre of Excellence for Translational Research in Public Health. The researchers gratefully acknowledge all the Type 2 diabetic patients and their household members who participated in the study for their contribution to this study; without them there would be no data. The researchers gratefully acknowledge the SDRN for providing the list of Type 2 diabetes and helping for sampling.
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BACKGROUND/OBJECTIVES: There is limited information to support definitive recommendations concerning the role of diet in the development of type 2 Diabetes mellitus (T2DM). The results of the latest meta-analyses suggest that an increased consumption of green leafy vegetables may reduce the incidence of diabetes, with either no association or weak associations demonstrated for total fruit and vegetable intake. Few studies have, however, focused on older subjects.
SUBJECTS/METHODS: The relationship between T2DM and fruit and vegetable intake was investigated using data from the NIH-AARP study and the EPIC Elderly study. All participants below the age of 50 and/or with a history of cancer, diabetes or coronary heart disease were excluded from the analysis. Multivariate logistic regression analysis was used to calculate the odds ratio of T2DM comparing the highest with the lowest estimated portions of fruit, vegetable, green leafy vegetables and cabbage intake.
RESULTS: Comparing people with the highest and lowest estimated portions of fruit, vegetable or green leafy vegetable intake indicated no association with the risk of T2DM. However, although the pooled OR across all studies showed no effect overall, there was significant heterogeneity across cohorts and independent results from the NIH-AARP study showed that fruit and green leafy vegetable intake was associated with a reduced risk of T2DM OR 0.95 (95% CI 0.91,0.99) and OR 0.87 (95% CI 0.87,0.90) respectively.
CONCLUSIONS: Fruit and vegetable intake was not shown to be related to incident T2DM in older subjects. Summary analysis also found no associations between green leafy vegetable and cabbage intake and the onset of T2DM. Future dietary pattern studies may shed light on the origin of the heterogeneity across populations.European Journal of Clinical Nutrition advance online publication, 17 August 2016;
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Purpose To examine patient-reported outcome (PRO) in a selected group of Swedish patients about to receive anti-vascular endothelial growth factor (VEGF) treatment for diabetic macular edema (DME). Material and methods In this cross-sectional study, 59 patients with diabetes mellitus, who regularly visited the outpatient eye-clinics, were included. Sociodemographic and clinical data were collected and the patients completed PRO measures before starting anti-VEGF treatment. PRO measures assessed eye-specific outcomes (NEI-VFQ-25) and generic health-related quality of life (SF-36). Results The participants consisted of 30 men and 29 women (mean age, 68.5 years); 54 (92 %) patients had type 2 diabetes; Five (9%) patients had moderate or severe visual impairment; 28 (47 %) were classified as having mild visual impairment. Some of the patients reported overall problems in their daily lives, such as with social relationships, as well as problems with impaired sight as a result of reduced distance vision. Conclusions Further studies are needed to investigate PRO factors related to low perceived general health in this patient population. It is important to increase our understanding of such underlying mechanisms to promote improvements in the quality of patient care.
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Background: type 2 diabetes mellitus includes changes in lifestyle in its etiology of prevention, but the evidence is clear —even when people know what to do and what they want to do, they simply do not adopt adherence behaviors. Structured education will allow improving not only metabolic control, but also the adjustment process to a new situation of disease, as well as to develop the patient’s skills in order to make him the key manager of his illness. Objectives: To determine patients’ adherence to prescribed therapeutic regimens. Material and methods: Quantitative, cross-sectional, non-experimental, descriptive, correlational study, with a sample of 102 people with type 2 diabetes, aged between 40 and 85 years old, mostly male (51.96%). The evaluation protocol included social-demographic and clinical questionnaire, Diabetes Self-care Scale and a questionnaire on Diabetes’ knowledge. We also used HbA1c in order to directly assess adherence. Results: It appears that there is no statistically signiicant correlation between socio-demographic variables such as gender and age and adherence. Variables, such as blood glucose monitoring, speciic diet compliance and knowledge, reveal a statistically signiicant effect on adherence (P < .05). Conclusion: The evidence is clear on the urgent need to recognize the importance of measuring patient adherence to a diabetes treatment plan for the maintenance of glycaemic control. We suggest the reinforcement of educational programs in people with type 2 diabetes so as to improve adherence to self-care.